Force-Aware Autonomous Robotic Surgery

TL;DR

This paper demonstrates that incorporating tool-tissue interaction force data into autonomous robotic surgery policies significantly improves success rates and tissue safety, especially on unseen tissues, using imitation learning with the da Vinci Research Kit.

Contribution

It introduces a force-aware autonomous policy for tissue retraction that outperforms vision-only policies in success and gentleness, leveraging force measurements in robot-assisted surgery.

Findings

Force policy is 3 times more successful on seen tissue

Force policy exerts 62% less force on tissue

Force policy is 3.5 times more successful on unseen tissue

Abstract

This work demonstrates the benefits of using tool-tissue interaction forces in the design of autonomous systems in robot-assisted surgery (RAS). Autonomous systems in surgery must manipulate tissues of different stiffness levels and hence should apply different levels of forces accordingly. We hypothesize that this ability is enabled by using force measurements as input to policies learned from human demonstrations. To test this hypothesis, we use Action-Chunking Transformers (ACT) to train two policies through imitation learning for automated tissue retraction with the da Vinci Research Kit (dVRK). To quantify the effects of using tool-tissue interaction force data, we trained a "no force policy" that uses the vision and robot kinematic data, and compared it to a "force policy" that uses force, vision and robot kinematic data. When tested on a previously seen tissue sample, the force policy is 3 times more successful in autonomously performing the task compared with the no force policy. In addition, the force policy is more gentle with the tissue compared with the no force policy, exerting on average 62% less force on the tissue. When tested on a previously unseen tissue sample, the force policy is 3.5 times more successful in autonomously performing the task, exerting an order of magnitude less forces on the tissue, compared with the no force policy. These results open the door to design force-aware autonomous systems that can meet the surgical guidelines for tissue handling, especially using the newly released RAS systems with force feedback capabilities such as the da Vinci 5.